Spectroscopic imaging is a topic that, of late, has received increased attention. A variety of factors have contributed to this recent surge in popularity, such as an increased appreciation and need for its application in, for example, materials analysis, the appearance of affordable array optical sensors, and the increased availability of economical computer power necessary to process the prodigious amount of data involved.
With regard to the computer power factor, consider the requirements for processing spectroscopic imaging data of a modestly high resolution scene over a relatively narrow bandwidth. A 576.times.384 CCD optical sensor array has 221,184 pixels. This is far fewer pixels than the typical IBM PC VGA 640.times.480 image format, and the high resolution CCD imagers are now commercially available with 4,000.times.4,000 pixels. Imaging over a typical wavelength band, for example, 400-800 nm, with modest resolution (10 nm), results in 40 data points per pixel. At 8 bits (1 byte) per data point, 8.8 megabytes of data per image frame is generated. At 30 frames per second for typical NTSC interlaced TV imagery, a computer is required to process (or at least store) 265 megabytes per second. A 30 second video clip then produces 8 gigabits of data. This is a prodigious data processing requirement for even modern PCs, and thus analysis of this volume of data in real time is simply an impossibility. Consequently, the only available choice is post (off-line) processing of the data.
Several techniques have been used in the past to, for example, map landscape for environmental purposes, such as plant species mapping, plant stress mapping, geological surveying, etc. The earliest and simplest technique was single point spectroradiometer measurements. This technique involves producing a map by conventional means, and then obtaining single point spectra at several map coordinates for analysis. Differences in absorption at different wavelengths could then be geographically related to the ground. Thus, for example, from a aerial photo of a stand of trees, a subsequent spectrum of a single point in the stand can be analyzed to confirm that the trees are spruce trees, and then an assumption can be made that the entire stand is spruce.
Imaging spectroradiometers can increase the spectral sample size to every pixel in the image. This is accomplished by using a high speed (high data rate) single point spectroradiometer to scan the scene to be imaged using an oscillating mirror. The imaging data, stored on computer tape, contains a complete spectrum of every pixel in the imaged scene, and only after off-line processing, can the data be remapped as an image of, for example, plant health color-coded on the map.
Earlier spectroradiometers used a limited number of wavelength bands over a spectral region of interest. This is because the least expensive and most readily available hardware was a filter wheel, which, in practical terms, is limited to the number of filters it can contain. Also, before very sensitive optical detectors were developed, more bandwidth per filter increased the image signal to noise ratio to an acceptable level. And finally, until more powerful computers were available, fewer filters meant less data per pixel, and thus a less burdensome volume of image data to process. Recent advances in imaging spectroradiometers involved the use of interferometers instead of filters. Interferometers provide a narrower bandwidth, that can be accommodated by fast detectors and computers capable of higher data rates. The inclusion of an interferometer adds expense and complexity to the system.
Other advances in spectroscopic imaging have employed programmable optical filters, such as acousto-optic tunable filters (AOTF) to select the light wavelength of interest, which is passed to a sensitive camera photodetector array. One example of using an AOTF optical filter as a wavelength selection device in imaging spectrophotometry is disclosed in U.S. Pat. No. 5,216,484, entitled REAL-TIME IMAGING SPECTROMETER. In the spectrometer of this patent, the AOTF is progressively tuned to scan a range of wavelengths, such as to produce a succession of camera image frames of a material or scene to be analyzed at a progression of different wavelengths. While the image frames are available for display in real time, the displayed images are difficult to interpret for analysis purposes.